code: def fw(self) -> None:
      self.out = torch.cat(
          [s[i].flatten() for s, i in zip(self.sources, self.indices)],
          dim=0,
      )
  
file_path: xformers/xformers/benchmarks/benchmark_indexing.py
imports: import random
  import torch
  from utils import DTYPE2STR, benchmark_main_helper2, product_dict
  import xformers.ops
label_desc: Use image node_id 1 for calling the IndexSelectBenchmarkBaseline obj's underlying member method code with example usage: obj.fw() without return types